Search Results - (( _ application ((tree algorithm) OR (max algorithm)) ) OR ( web applications a algorithm ))

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    An optimized attack tree model for security test case planning and generation by Omotunde, Habeeb, Ibrahim, Rosziati, Ahmed, Maryam

    Published 2018
    “…This paper presents an attack tree modeling algorithm for deriving a minimal set of effective attack vectors required to test a web application for SQL injection vulnerabilities. …”
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    Article
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    Car dealership web application by Yap, Jheng Khin

    Published 2022
    “…In this project, a web application and a web service were proposed and implemented. …”
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    Final Year Project / Dissertation / Thesis
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    Cyberbullying detection: a machine learning approach by Yeong, Su Yen

    Published 2022
    “…Machine learning is a hot topic and it is widely implemented in software, web application and more. …”
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    Final Year Project / Dissertation / Thesis
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    Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud by Mahmud, Nur Farahana

    Published 2022
    “…The objectives of this research are to develop a Malaysian license plate recognition system using a Convolutional Neural Network (CNN) on a web application and evaluate the performance of the system based on accuracy and loss values. …”
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    Student Project
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    An improved framework for content and link-based web spam detection: a combined approach by Shahzad, Asim

    Published 2021
    “…The content-based web spam detection framework uses three proposed and two improved content-based algorithms for web spam detection. …”
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    Thesis
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    Content-based recommender system for an academic social network / Vala Ali Rohani by Vala Ali, Rohani

    Published 2014
    “…The algorithm exploits all interests and preferences in a hierarchy tree structure. …”
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    Thesis
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    Defect green coffee bean detection using image recognition and supervised learning by Shafian Izan Sofian

    Published 2022
    “…Therefore, in this research project, the process will be conducted by using an image classifier with the model of a machine learning algorithm which the candidates comprise of Support Vector Machine, k-Nearest Neighbour and Decision Tree. k-nearest neighbour has the highest F1-score (0.51) than the other two algorithms (Support Vector Machine: 0.50, and Decision Tree: 0.48). …”
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    Academic Exercise
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    Comparative study of machine learning algorithms in data classification by Tan, Kai Jun

    Published 2025
    “…The results will help with real-world data mining applications of machine learning and be a useful guide for further study and practical applications.…”
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    Final Year Project / Dissertation / Thesis
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    Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Ahmad Salihin, Samsudin, Amir Izzani, Mohamed, Mohd Mawardi, Saari

    Published 2025
    “…A comprehensive data preprocessing pipeline was implemented, including missing value treatment, outlier removal, and feature normalization using Min-Max scaling. Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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    Article
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    Interference avoidance routing and scheduling using multiple transceivers for IEEE 802.16 mesh network by Qasem, Yaaqob Ali Ahmed

    Published 2010
    “…These algorithms have two advantages: first, they avoid the collision with neighbouring nodes. …”
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    Thesis
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    Context-Aware Recommender System based on machine learning in tourist mobile application / Nor Liza Saad … [et al.] by Saad, Nor Liza, Khairudin, Nurkhairizan, Azizan, Azilawati, Abd Rahman, Abdullah Sani, Ibrahim, Roslina

    Published 2022
    “…Based on usability study, most users agreed that the tourist mobile application is easier and useful for them. From the machine learning evaluation, Random Forest algorithm has generated the most accurate prediction compared to Decision Tree, Logistic Regression and Generalized Linear Model. …”
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    Article